保險公司清償能力一直是保險監理的重心，在所有現行的制度中風險基礎資本是最重要的，但此項制度仍有其缺點，因此其他動態分析模型被許多學者所提出，如涉險值及情境分析。雖然這些動態分析模型被學者所偏好，但監理機關仍須對這些模型的精確程度加以了解，這也是本篇論文所要研究的目的。 基於此，本篇論文以模擬方式及經濟模型加以分析風險基礎資本、情境分析及涉險值等方法的破產預測的相對精確性。其中風險基礎資本完全採用現有NAIC的年報資料，情境分析及涉險值則採用我們所建立的模型，基於此也可以確認現有監理制度是否有缺失。 我們的結果發現風險基礎資本的預測能力很低，動態模型-情境分析及涉險值皆優於風險基礎資本，且在不同動態模型中涉險值的預測能力較好。因此可知被學者所偏好的動態分析模型應是未來保險監理的方向希望藉由本篇提供監理機關一個參考的依據。 / Solvency prediction of insurers has been the focus of insurance regulation. Among the solvency regulation systems, risked-based capital (RBC) is the most important but RBC still has some drawbacks. Thus, the dynamic financial analyses-scenario analysis and Value at Risk have been developed to be the regulation tool. Although, the scholars prefer the dynamic financial analysis, the regulators still want to make sure the accuracy of dynamic financial analysis. That is the purpose of our paper. Therefore, we use the simulation result and the econometric model to analyze the relative effectiveness of RBC, scenario and Value at Risk (VaR). The RBC is from the annual statement and the scenario and VaR come from our simulation model. Our result shows that the RBC has very low explanatory power, the dynamic financial analysis is better than RBC, and VaR outperform scenario analysis. Thus, we conclude that VaR is the way to go for property-casualty insurance regulators.